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From: jonathan <johnscpg@googlemail.com>
Newsgroups: comp.lang.ada
Subject: Re: Copying rows in a two dimensional array.
Date: Sun, 14 Feb 2010 08:16:06 -0800 (PST)
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On Feb 14, 1:54=A0am, Hibou57 (Yannick Duch=EAne)
<yannick_duch...@yahoo.fr> wrote:
> Le Sun, 14 Feb 2010 01:42:13 +0100, jonathan <johns...@googlemail.com> a =
=A0
> =E9crit:

  First example: we eigen-decompose an N x N =3D 2048 x 2048 matrix.
  The data storage matrix is M x M =3D (1024+Padding) x (1024+Padding)

should be of course:

  First example: we eigen-decompose an N x N =3D 2048 x 2048 matrix.
  The data storage matrix is M x M =3D (2048+Padding) x (2048+Padding)

> Do not know if you already know this document (as I remember I picked it =
=A0
> up from some one thread at comp.lang.ada), I've talked about on the other=
 =A0
> fr.c.l.a :http://research.scee.net/files/presentations/gcapaustralia09/Pi=
tfalls...
> I had pointed about frames =A0#17, #18, #19 et #20, which contains good =
=A0
> source of inspiration. Hope this could help you to figure a path.

Yes, I remembered this, probably from an old post of yours.  I wanted
to cite it when
when I posted earlier, but I could not find the site.  This is not
something you
forget quickly (frames 17 and 18):

   1980: RAM latency ~ 1 cycle
   2009: RAM latency ~ 400+ cycles

It's the heart of the matter, and it is just getting worse.  Helps
convince me
anyway that I did not waste time on an unimportant matter! In
numerical linear
algebra the usual solution is to restructure matrices as a collection
of
blocks.  That has a few of its own problems though. Minor footnote: I
did
some tests on Intel's new nehalem CPU's.  Vastly improved performance
on these
multi-megabyte arrays.  Problem not cured though. Don't know enough to
say more about it.
Thanks for the reminder.

Jonathan